AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Monitoring, Ambulatory

Showing 71 to 80 of 118 articles

Clear Filters

Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures.

Movement disorders : official journal of the Movement Disorder Society
For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qua...

Autoregressive-moving-average hidden Markov model for vision-based fall prediction-An application for walker robot.

Assistive technology : the official journal of RESNA
Population aging of the societies requires providing the elderly with safe and dependable assistive technologies in daily life activities. Improving the fall detection algorithms can play a major role in achieving this goal. This article proposes a r...

Developing a Wearable Ankle Rehabilitation Robotic Device for in-Bed Acute Stroke Rehabilitation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Ankle movement training is important in motor recovery post stroke and early intervention is critical to stroke rehabilitation. However, acute stroke survivors receive motor rehabilitation in only a small fraction of time, partly due to the lack of e...

Sequence Learning with Passive RFID Sensors for Real-Time Bed-Egress Recognition in Older People.

IEEE journal of biomedical and health informatics
Getting out of bed and ambulating without supervision is identified as one of the major causes of patient falls in hospitals and nursing homes. Therefore, increased supervision is proposed as a key strategy toward falls prevention. An emerging genera...

Stress Detection Using Wearable Physiological and Sociometric Sensors.

International journal of neural systems
Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detection of stress of people in a social situation by combining two sensor systems that capture physio...

Evaluation of an Assistive Telepresence Robot for Elderly Healthcare.

Journal of medical systems
In this paper we described the telepresence robot system designed to improve the well-being of elderly by supporting them to do daily activities independently, to facilitate social interaction in order to overcome a sense of social isolation and lone...

Bigdata Oriented Multimedia Mobile Health Applications.

Journal of medical systems
In this paper, two mHealth applications are introduced, which can be employed as the terminals of bigdata based health service to collect information for electronic medical records (EMRs). The first one is a hybrid system for improving the user exper...

Design of a heart rate controller for treadmill exercise using a recurrent fuzzy neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In this study, we developed a computer controlled treadmill system using a recurrent fuzzy neural network heart rate controller (RFNNHRC). Treadmill speeds and inclines were controlled by corresponding control servo motors. ...

A Hierarchical Classification and Segmentation Scheme for Processing Sensor Data.

IEEE journal of biomedical and health informatics
Detecting short-duration events from continuous sensor signals is a significant challenge in the domain of wearable devices and health monitoring systems. Time-series segmentation refers to the challenge of subdividing a continuous stream of data int...

A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington's Disease Patients.

Sensors (Basel, Switzerland)
Machine learning methods have been widely used for gait assessment through the estimation of spatio-temporal parameters. As a further step, the objective of this work is to propose and validate a general probabilistic modeling approach for the classi...